A method for de-icing wind turbine blades

Abstract

The application relates to the technical field of wind power blade maintenance, and discloses a wind power blade anti-icing treatment method, which comprises the following steps: S1: constructing a multi-dimensional working condition sensing network, collecting blade icing parameters, environmental parameters and unit operation parameters in real time, wherein the icing parameters include the icing thickness and the icing type of different regions of the blade, the environmental parameters include air density, environmental temperature and liquid water related parameters in the air, and the unit operation parameters include the blade rotating speed and the blade root load; S2: constructing a working condition judgment model based on the collected parameters, outputting an anti-icing trigger signal and a cooperative control strategy, wherein the cooperative control strategy comprises an anti-icing mode and an ice removal mode. The wind power blade anti-icing treatment method can realize multi-field coupling cooperation of ultrasonic vibration, gradient electrothermal and aerodynamic disturbance, and can realize differential regulation and control according to the icing characteristics of different regions of the blade, so that the anti-icing efficiency is significantly improved compared with the existing single technology or simple combined technology.

Description

Technical Field

[0001] This invention relates to the field of wind turbine blade maintenance technology, specifically a method for preventing and de-icing wind turbine blades. Background Technology

[0002] Wind turbine blades are the core components of wind turbine generators for capturing and converting wind energy. Their aerodynamic shape and surface condition directly determine the generator's power generation efficiency and operational stability. With the expansion of the wind power industry, blade icing has become increasingly prominent. In low-temperature environments, liquid water in the air freezes rapidly upon contact with the blade surface, forming an ice layer that covers the blade surface. This ice layer alters the original airfoil structure of the blade, increases surface roughness, and leads to a decrease in lift and an increase in drag. This not only significantly reduces the generator's power generation efficiency but also causes uneven stress on the blade, which can exacerbate structural fatigue over long-term operation.

[0003] Existing wind turbine blade anti-icing technologies mainly include electrothermal anti-icing and vibration de-icing. Electrothermal anti-icing melts the ice layer by heating the blade surface, but it consumes a lot of energy and the heat distribution is uneven. Vibration de-icing relies on vibration to peel off the ice layer, but its effect on peeling off dense ice layers is limited, and high-frequency vibration will aggravate blade structural fatigue.

[0004] Therefore, we propose a method for preventing and de-icing wind turbine blades to solve the above problems. Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] To address the shortcomings of existing technologies, this invention provides a wind turbine blade anti-icing and de-icing treatment method that has the advantages of accurately sensing the blade icing status, environmental conditions, and unit operating status, and dynamically switching between anti-icing and de-icing modes according to actual operating conditions. This solves the problems of low efficiency, high energy consumption, easy damage to blade structure, and difficulty in adapting to dynamic operating conditions in existing wind turbine blade anti-icing and de-icing technologies.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for anti-icing and de-icing wind turbine blades, comprising the following steps:

[0009] S1: Construct a multi-dimensional operating condition sensing network to collect blade icing parameters, environmental parameters and unit operating parameters in real time. The icing parameters include the icing thickness and icing type in different areas of the blade. The environmental parameters include air density, ambient temperature and parameters related to liquid water in the air. The unit operating parameters include blade speed and blade root load.

[0010] S2: Construct a working condition judgment model based on the collected parameters, and output anti-icing and de-icing trigger signals and collaborative control strategies. The collaborative control strategies include anti-icing mode and de-icing mode, which are triggered according to the combination of ice thickness and ambient temperature.

[0011] S3: Activate the multi-field coupled collaborative execution system, which includes an ultrasonic vibration module, a gradient electrothermal module and an aerodynamic turbulence module. Based on the collaborative control strategy, it implements differentiated regulation of different areas of the blade to achieve anti-icing or de-icing operations.

[0012] S4: Monitors the control effect and unit safety parameters in real time, dynamically iterates and corrects the control parameters until the preset conditions are met, and then switches to standby anti-icing state.

[0013] Preferably, the multi-dimensional operating condition sensing network in step S1 includes icing parameter sensors embedded in different areas of the blade, environmental parameter sensors set in the nacelle, temperature sensors arranged on the blade surface, and load sensors installed at the blade root. The collected data is processed by a filtering algorithm to remove interference signals.

[0014] Preferably, the judgment logic of the working condition judgment model in step S2 includes: determining whether to enter the anti-icing warning state based on the ambient temperature and related parameters of liquid water in the air; determining whether to trigger the anti-icing mode or the de-icing mode based on the ice thickness; and determining whether to activate the load compensation adaptation strategy based on the change in air density.

[0015] Preferably, the control method of the ultrasonic vibration module in step S3 is dynamically adjusted according to the operating mode. In the de-icing mode, vibration parameters adapted to ice peeling are used, and in the anti-icing mode, vibration parameters adapted to ice adhesion suppression are used. Furthermore, the vibration-related parameters are adjusted according to the type of icing.

[0016] Preferably, the gradient electrothermal module in step S3 adopts a zoned temperature control design. The electrothermal power density and heating temperature of different areas of the blade are set differently according to the operating mode. The temperature is maintained stable through a closed-loop control algorithm to avoid local overheating.

[0017] Preferably, the aerodynamic turbulence module in step S3 is implemented by an embedded turbulence component on the blade surface. When activated in de-icing mode, it generates local airflow turbulence to disrupt the bonding force between the ice layer and the blade surface, forming a synergistic peeling effect with the ultrasonic vibration module.

[0018] Preferably, the dynamic iterative correction logic in step S4 includes: adjusting the operating parameters of the ultrasonic vibration module and the gradient electrothermal module according to the change in icing thickness; adjusting the operating parameters of the blade rotation speed and the aerodynamic turbulence module according to the change in blade root load; and after the preset icing thickness condition is reached, shutting down some functional modules and retaining only the anti-icing function of local areas.

[0019] Preferably, the load compensation adaptation strategy adjusts the blade drag coefficient and rotational speed parameters based on real-time air density to balance de-icing effect, unit operation safety and power generation efficiency.

[0020] (III) Beneficial Effects

[0021] Compared with the prior art, the present invention provides a method for anti-icing and de-icing wind turbine blades, which has the following beneficial effects:

[0022] 1. The wind turbine blade anti-icing and de-icing treatment method, through the multi-field coupling and synergy of ultrasonic vibration, gradient electrothermal and aerodynamic turbulence, combined with the differentiated control of icing characteristics in different areas of the blade, significantly improves the anti-icing and de-icing efficiency compared with existing single technology or simple combination technology. It can quickly peel off the formed ice layer, effectively inhibit the adhesion of new ice layer, and avoid the problems of excessive energy consumption or structural damage caused by single technology.

[0023] 2. This wind turbine blade anti-icing and de-icing treatment method achieves real-time adaptation to environmental conditions, icing status, and unit operating status through multi-dimensional operating condition perception and dynamic iterative correction mechanism. It not only solves the shortcomings of existing technologies in dealing with dynamic operating conditions, but also avoids the risk of unit overload caused by changes in operating conditions through load compensation and adaptation strategy. While ensuring the anti-icing and de-icing effect, it also takes into account the balance between unit operating safety and power generation efficiency. Attached Figure Description

[0024] Figure 1 This is a schematic flowchart of a wind turbine blade anti-icing and de-icing treatment method proposed in this invention. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Please see Figure 1 A method for preventing and de-icing wind turbine blades includes the following steps:

[0027] Step S1: Construction and parameter acquisition of a multi-dimensional operating condition sensing network. First, corresponding icing parameter sensors are embedded in different areas of the wind turbine blade, such as the leading edge, middle, and tip, to detect the icing thickness and type in each area in real time. An environmental parameter sensor is installed on the top of the nacelle to collect parameters related to air density, ambient temperature, and liquid water in the air. Temperature sensors are arranged on the blade surface to monitor the surface temperature distribution in real time. A load sensor is installed at the blade root to collect root load data during blade operation. Each sensor continuously collects data at a preset frequency. The raw data is transmitted to the control unit and then denoised using a filtering algorithm to remove invalid signals caused by environmental interference and sensor errors, obtaining accurate and reliable operating condition parameters to provide data support for subsequent operating condition determination.

[0028] Step S2: Operating condition judgment model operation and control strategy output. The control unit has a built-in operating condition judgment model, which makes logical judgments based on the effective parameters collected in step S1: When the ambient temperature meets the low temperature condition and the relevant parameters of liquid water in the air reach the preset threshold, the system is judged to enter the anti-icing warning state and prepare for anti-icing and de-icing. When the blade ice thickness is detected to be in a low range, the anti-icing mode is triggered to inhibit the further thickening of the ice layer. When the ice thickness reaches a high range or the blade root load reaches the preset safety threshold, the de-icing mode is triggered to quickly remove the formed ice layer. If the air density changes significantly from the standard state at the same time as the anti-icing or de-icing mode is triggered, the load compensation adaptation strategy is started simultaneously to avoid the unit from overload caused by the change in operating conditions. According to the above judgment results, the operating condition judgment model outputs the corresponding collaborative control strategy, which clarifies the start-up status, working parameters and control logic of each functional module.

[0029] Step S3: Start-up and zoned control of the multi-field coupled collaborative execution system. The collaborative execution system includes an ultrasonic vibration module, a gradient electrothermal module, and an aerodynamic turbulence module. Each module performs corresponding operations according to the collaborative control strategy: The ultrasonic vibration module adjusts its working state according to the operating mode. In anti-icing mode, low-intensity vibration parameters are used to inhibit water vapor from freezing and adhering to the blade surface. In de-icing mode, high-intensity vibration parameters are used to generate vibration energy that acts on the bonding surface between the ice layer and the blade, thereby breaking the bonding force. At the same time, the vibration parameters are finely adjusted according to the type of icing to improve the peeling effect.

[0030] The gradient heating module adopts a zoned temperature control design. Different heating power densities and heating temperatures are set according to the differences in the probability and degree of icing in areas such as the leading edge, middle, and root of the blade. In anti-icing mode, a lower heating temperature is maintained to avoid energy waste. In de-icing mode, the heating temperature is appropriately increased to accelerate the melting of ice. At the same time, the heating power is adjusted in real time through a closed-loop control algorithm to ensure temperature stability and prevent local overheating damage to the blade material.

[0031] The aerodynamic turbulence module is activated only in de-icing mode. Embedded turbulence components on the blade surface open and close according to a preset pattern, generating local airflow disturbances. This further disrupts the bond between the ice layer and the blade surface, creating a synergistic effect with the ultrasonic vibration module to improve ice removal efficiency. This is especially effective for areas such as blade tips where ice is difficult to remove, thus enhancing the de-icing effect.

[0032] Step S4: Real-time monitoring and dynamic iterative correction. During the execution of step S3, the multi-dimensional operating condition sensing network continuously collects parameters such as blade icing thickness, surface temperature, and blade root load to monitor the anti-icing effect and the safe operating status of the unit in real time. If the icing thickness is gradually reduced to the preset safe range and the blade root load is within the safe range, the control unit gradually adjusts the working parameters of each functional module through dynamic iterative correction logic, reducing the ultrasonic vibration intensity and the electrothermal power. When the icing thickness drops to the preset target value, the ultrasonic vibration module and the aerodynamic turbulence module are turned off, and only the gradient electrothermal module in the blade root area is kept in low-power operation, switching to standby anti-icing state to continuously suppress ice adhesion. If the icing thickness does not decrease or the blade root load exceeds the safe threshold, the working parameters of each module are adjusted in a timely manner, such as increasing the ultrasonic vibration intensity, increasing the electrothermal temperature, adjusting the turbulence frequency, or optimizing the blade speed, until the icing thickness and the unit load meet the safety requirements.

[0033] It should be noted that the term "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0034] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for preventing and de-icing wind turbine blades, comprising the following steps: S1: Construct a multi-dimensional operating condition sensing network to collect blade icing parameters, environmental parameters and unit operating parameters in real time. The icing parameters include the icing thickness and icing type in different areas of the blade. The environmental parameters include air density, ambient temperature and parameters related to liquid water in the air. The unit operating parameters include blade speed and blade root load. S2: Construct a working condition judgment model based on the collected parameters, and output anti-icing and de-icing trigger signals and collaborative control strategies. The collaborative control strategies include anti-icing mode and de-icing mode, which are triggered according to the combination of ice thickness and ambient temperature. S3: Activate the multi-field coupled collaborative execution system, which includes an ultrasonic vibration module, a gradient electrothermal module and an aerodynamic turbulence module. Based on the collaborative control strategy, it implements differentiated regulation of different areas of the blade to achieve anti-icing or de-icing operations. S4: Monitors the control effect and unit safety parameters in real time, dynamically iterates and corrects the control parameters until the preset conditions are met, and then switches to standby anti-icing state.

2. The method for preventing and de-icing wind turbine blades according to claim 1, characterized in that: The multi-dimensional operating condition sensing network in step S1 includes icing parameter sensors embedded in different areas of the blade, environmental parameter sensors set in the nacelle, temperature sensors arranged on the blade surface, and load sensors installed at the blade root. The collected data is processed by a filtering algorithm to remove interference signals.

3. The method for preventing and de-icing wind turbine blades according to claim 1, characterized in that: The judgment logic of the working condition judgment model in step S2 includes: determining whether to enter the anti-icing warning state based on the ambient temperature and related parameters of liquid water in the air; determining whether to trigger the anti-icing mode or the de-icing mode based on the ice thickness; and determining whether to activate the load compensation adaptation strategy based on the change in air density.

4. The method for preventing and de-icing wind turbine blades according to claim 1, characterized in that: The control method of the ultrasonic vibration module in step S3 is dynamically adjusted according to the operating mode. In the de-icing mode, vibration parameters adapted to ice peeling are used, and in the anti-icing mode, vibration parameters adapted to ice adhesion suppression are used. Furthermore, the vibration-related parameters are adjusted according to the type of icing.

5. The method for preventing and de-icing wind turbine blades according to claim 1, characterized in that: The gradient electrothermal module described in step S3 adopts a zoned temperature control design. The electrothermal power density and heating temperature of different areas of the blade are set differently according to the operating mode. The closed-loop control algorithm maintains temperature stability and avoids local overheating.

6. The method for preventing and de-icing wind turbine blades according to claim 1, characterized in that: The aerodynamic turbulence module described in step S3 is implemented through embedded turbulence components on the blade surface. It is activated in de-icing mode to generate local airflow turbulence to break the bonding force between the ice layer and the blade surface, forming a synergistic peeling effect with the ultrasonic vibration module.

7. The method for preventing and de-icing wind turbine blades according to claim 1, characterized in that: The dynamic iterative correction logic in step S4 includes: adjusting the operating parameters of the ultrasonic vibration module and the gradient electrothermal module according to the change in icing thickness; adjusting the operating parameters of the blade rotation speed and the aerodynamic turbulence module according to the change in blade root load; and after the preset icing thickness condition is reached, shutting down some functional modules and retaining only the anti-icing function of local areas.

8. The method for preventing and de-icing wind turbine blades according to claim 3, characterized in that: The load compensation and adaptation strategy adjusts the blade drag coefficient and rotational speed parameters based on real-time air density to balance de-icing effect, unit operation safety and power generation efficiency.

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